—This paper studies the problem of outlier detection on uncertain data. We start with a comprehensive model considering both uncertain objects and their instances. An uncertain o...
In Analytic Hierarchy Process (AHP) structured hierarchically as several criteria and alternatives, the priority of an alternative is obtained by using the pairwise comparisons ba...
Abstract. Robust Optimization (RO) is a modeling methodology, combined with computational tools, to process optimization problems in which the data are uncertain and is only known ...
Large databases with uncertain information are becoming more common in many applications including data integration, location tracking, and Web search. In these applications, ranki...
The precise specification of reward functions for Markov decision processes (MDPs) is often extremely difficult, motivating research into both reward elicitation and the robust so...